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You're reading from  Network Science with Python and NetworkX Quick Start Guide

Product typeBook
Published inApr 2019
Reading LevelIntermediate
PublisherPackt
ISBN-139781789955316
Edition1st Edition
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Edward L. Platt
Edward L. Platt
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Edward L. Platt

Edward L. Platt creates technology for communities and communities for technology. He is currently a researcher at the University of Michigan School of Information and the Center for the Study of Complex Systems. He has published research on large-scale collective action, social networks, and online communities. He was formerly a staff researcher at the MIT Center for Civic Media. He contributes to many free/open source software projects, including tools for media analysis, network science, and cooperative organizations. He has also done research on quantum computing and fault tolerance. He has an M.Math in Applied Mathematics from the University of Waterloo, as well as B.S degrees in both Computer Science and Physics from MIT.
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Cliques

In the densest neighborhoods of a network, it is sometimes possible to find groups of nodes that are all connected to each other. Such groups are called cliques. Identification of cliques is another way to analyze the medium-scale structure of a network. Because cliques are highly interconnected, the nodes in a clique rarely belong to different communities. In fact, cliques often form the cores of communities.

Chapter 4, Affiliation Networks, described how to transform an affiliation network into a single-mode network using projections. For each node removed by such projections, its neighbors are connected into a clique. Cliques can give clues to an underlying affiliation network structure.

NetworkX provides the find_cliques() function to find cliques in a network. This function returns an iterator over all cliques in an arbitrary order. For example, using this function...

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Network Science with Python and NetworkX Quick Start Guide
Published in: Apr 2019Publisher: PacktISBN-13: 9781789955316

Author (1)

author image
Edward L. Platt

Edward L. Platt creates technology for communities and communities for technology. He is currently a researcher at the University of Michigan School of Information and the Center for the Study of Complex Systems. He has published research on large-scale collective action, social networks, and online communities. He was formerly a staff researcher at the MIT Center for Civic Media. He contributes to many free/open source software projects, including tools for media analysis, network science, and cooperative organizations. He has also done research on quantum computing and fault tolerance. He has an M.Math in Applied Mathematics from the University of Waterloo, as well as B.S degrees in both Computer Science and Physics from MIT.
Read more about Edward L. Platt